1. Technical Field
The present invention relates to a method for adjusting image, and more particularly to a method for adjusting image capable of improving an adjustment performance by using lower hardware resources.
2. Related Art
With the rapid progress of technology, liquid crystal displays or plasma display has replaced conventional cathode-ray tube (CRT) displays. Furthermore, the LCD displays has been widely applied to electronic products having different sizes. However, when multimedia devices play video media, the brightness, contrast, and color saturation of the screens are not always at optimum values. In addition, the video image frame is sometimes bright and sometimes dark, and the color saturation is also changed at any time, such that when playing the video image, the device has to dynamically and appropriately adjust the brightness, contrast, and color saturation, so as to achieve an optimum displaying performance.
The current image processing technology has many different image frame adjusting methods, but such image frame adjusting methods can not bring high image quality with the lower hardware resources. Certain correction methods achieving better image frame quality cannot be applied to the models having hardware resources, especially portable electronic products. Nowadays, the common methods for adjusting image include a single curve method, a dynamic curve method, and a quasi high dynamic range (quasi-HDR) method.
In the single curve method, an image signal value of each pixel in an input image is substituted to an image signal value adjusting curve equation, so as to adjust the image signal value of each pixel, thereby achieving an image reinforcement conversion. Each pixel is adjusted through the single image signal value adjusting curve equation, such that lower hardware resources are consumed, which can be achieved even if the processor has a low performance. However, by only using the single image signal value adjusting curve equation, the variations in response to properties of films and relations among the image frames cannot be realized, so that the reinforcement effect is not distinct.
The dynamic curve method is similar to the single curve method, except that the dynamic curve method uses a plurality of image signal value adjusting curve equations. Before an image is adjusted, the image is analyzed and a curve equation most suitable for the current image is selected, and then the image signal values of the image are substituted to the selected curve equation for adjustment. As compared with the single curve method, the dynamic curve method can make further adjustment according to properties of the image frames and the film, thereby achieving the better effect. However, before the adjustment, the image must be analyzed first, such that higher hardware resources are required.
In the quasi-HDR method, according to the attributes of the image, only a part of the image is adjusted. For example, under a state of not adjusting the bright parts of the image, only the brightness of the dark parts is improved, thereby eliminating the over-dark regions in the image frame. The quasi-HDR method is usually used in a post-process of the pictures, and may show the excellent effect under the single image frame, but when the image frames are continuously played, the image frame may have redundant changes (for example, light halo). The major disadvantage of the quasi-HDR lies in requiring great hardware resources, such that high-level processors must be used together.